Performance of stock markets is determined by three classes of variables: macroeconomic indicators, industry & firm heterogeneity and third country effects. When assessing performance of a stock market index, impact of industry & firm heterogeneity is marginal as it is already embedded in the index through its constituent companies. This paper will therefore focus on the other two. Chinese stock market was selected as an application as their performance compared to other domestic indicators (mainly GDP growth) is considered inferior by many researchers. Using econometric framework for panel data and a Bayesian extension, the paper estimates multiple models of Chinese stock market performance examining individual determinants of it. Subsequently, it predicts development of theoretical prices of two main Chinese stock indices on two time samples until 2013. The paper then demonstrates underperformance of Chinese stock market by comparing the modeled prices to actual prices realized on the market. JEL Classification C23, C51, C53, G15, G17 Keywords underperformance, panel data, fixed effects model, Bayesian Model Averaging Author's e-mail roman_kovac@ymail.com Supervisor's e-mail karel.bata@seznam.cz

Internal migration has frequently been subject of empirical research. This study attempts to find a relationship between international immigration and internal out-migration in all German states, covering the time period between 1993 and 2016. The underlying theories were established by Card et al. (2008), Schlömer (2012), Florida (2002) and Chiswick and Miller (2015). These were used to develop a modified version of the gravity model. The dataset was received from the Federal Statistical Office of Germany (Statistisches Bundesamt). The regressions were executed using a fixed effects model and a pooled OLS as a robustness check. The empirical findings suggest no evidence of a statistically significant effect of international immigration on internal out-migration patterns in the covered period. Control variables suggest policymakers to focus on other factors when the effects of immigration policies on internal out-migration are being considered.

This paper investigates what factors affect the destination choice for Jordanian to 8 countries (Oman, Saudi Arabia, Syria, Tunisia, Yemen, Egypt, Lebanon and Bahrain) using panel data analysis. Number of outbound tourists is represented as dependent variable, which is regressed over five explanatory variables using fixed effect model. The finding of this paper is that tourists from Jordan have weak demand for outbound tourism; Jordanian decision of traveling abroad is determined by the cost of traveling to different places and choosing the cheapest alternative.

Many studies suggest the ability of the NAIC Risk-Based Capital ratio (RBC ratio) to predict insurer insolvency. Based on the US life insurer (insurer) data for the period of 2005 to 2008, this study finds explanatory variables that have a statistically significant relationship with the RBC ratio. Advantages of panel data over cross-sectional and time series data analysis are exploited to make valid inference on coefficients of the explanatory variables. Testing for unobserved insurer and time effects and for dependence between these effects and the explanatory variables indicates the appropriateness of the fixed insurer and time effects model. Based on the ordinary least squares estimates, it is found that insurers' size, capital-to-asset ratio, and return on capital have a statistically significant relationship with the RBC ratio. Additionally, health product, annuity product, opportunity, and regulatory risks of insurers are related to the RBC ratio. Accounting for heteroscedasticity and autocorrelation for a given insurer yields the same coefficient estimates, but increased standard errors. / text

This thesis investigates the relationship between Tobin’s Q and regional housing investment in Sweden for the time period of 1998-2012. The relationship is tested through estimation of two models for time-series analysis, a vector error correction model (VECM) and an autoregressive distributed lag (ARDL) model. Depending on which model that is used, I find some evidence of positive correlation between Tobin’s Q and regional housing investment in the long run while the short run dynamics of investment does not seem to be explained by Tobin’s Q. By transforming the regional data into a panel data set and running a fixed effects model, I examine the gain in explanatory power of Tobin’s Q from using disaggregated data rather than aggregated. My findings suggest that using disaggregated data improves the explanatory power of Tobin’s Q on investment. However, the Granger Causality test indicates two-way causality between Tobin’s Q and investment, causing endogeneity problem in the estimated equations.

This paper addresses the pressing problem of the surge in crime in Sweden, which has led to substantial uncertainty about its underlying causes. By investigating the correlation between socio-economic factors and crime on a municipality level from 2015 to 2020, we aim to provide valuable insights into understanding and effectively tackling this issue. Specifically, we examine the role of male immigrants, income, education level, and population density, contributing to the field of economics by shedding light on potential economic policies that can effectively reduce overall crime rates. Additionally, we focus on gun violence, considering Sweden's notorious reputation in recent years, to comprehensively analyze the relationship between these factors and crime. Our empirical analysis, employing the Fixed Effects Model and Pearson Correlation Matrix, explores these connections, revealing both inconclusive evidence regarding the link between immigration and crime and ambiguous conclusions for the remaining independent variables. These findings have important implications for policymakers striving to address the urgent problem of rising crime in Sweden.

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Managers are coming under increasing pressure from a wide array of stakeholders to improve the environmental performance of their firms while still achieving financial performance objectives. One of the most researched questions in the business and the natural environment (B&NE) literature is whether it pays to be green. Despite more than three decades of research, scholars have been unable to clearly answer this question. The purpose of this dissertation was to attempt to identify the antecedents that lead to increased, firm-level environmental performance and the conditions in which firms are then able to profit from enhanced environmental performance. First, I assessed three intra-organizational factors of top management teams (i.e. female representation, concern for non-financial stakeholders, and risk-seeking propensity) that theory indicated are associated with increased corporate environmental performance (CEP). Theory also leads us to believe that top management teams with these attributes should perform better in dynamic settings, so I tested to see if industry dynamism moderates these relationships. Second, I then examined industry-level forces that theory indicates would moderate the relationship between CEP and corporate financial performance (CFP). These moderating forces include industry profitability, industry dynamism, and the degree of industry environmental regulation. Hypotheses were tested using panel data obtained from the KLD, Compustat, and Environmental Protection Agency databases for the years 2000 to 2011. The sample consists of firms comprising the Standard and Poor’s 500 and was analyzed using fixed-effect regression and moderating variables were analyzed using the Johnson-Neyman technique.

African countries have over the last few decades, experienced a thorny path towards sustained economic growth. Quite a number of researchers have opined that a major factor responsible for their stunted growth path is the prevalence of corruption in the governments of many African countries. However, a group of scholars, called revisionists, have suggested that corruption actually acts as grease in the wheel that ensures the smooth running of an economy, by providing a mechanism to evade inefficient bureaucratic procedures and allow more equitable representation of minority members of the society. With the increasing exposure of African economies to the international community, there is a need to examine the obtainable evidence in relation to corruption and economic growth in African countries. This thesis, therefore, aims to establish the nature of the relationship between corruption and economic growth in the selected African countries. The growth rate of gross domestic product per capita is used to represent the variable, economic growth. The study employs the use of panel data fixed effects and random effect estimation techniques, across 18 countries, over the period of 1997 – 2016. The results show that corruption has a positive relationship with economic growth in the selected African countries. This is in line with the grease in the wheel argument for corruption proposed by revisionists. The results also indicate that corruption has a moderately significant impact on economic growth at 10% level of significance. The literature review suggests that corruption affects economic growth directly and indirectly through mechanisms such as investment (private and public), human capital, openness, and institutional mechanisms, among others.

This paper investigates the determinants of excess returns using dividend yields as a proxy in a cross-sectional setting. First, we find that types of industry and the current business cycle are determining factors of returns. Second, our results suggest that dividend yield serves a signaling mechanism indicating “healthiness” of a firm among prospective investors. Third we see that there is a positive relationship between dividend yield and risk, especially in the utility and financial sectors. And finally, using actual excess returns, instead of dividend yield in our model shows that all predictors of dividend yield were also significant predictors of excess returns. This connection between dividend yield and excess returns support our use of dividend yield as a proxy for excess returns.